Brain data#

This section presents results of brain MRI data. Below are quantitative T1 values computed using the MP2RAGE and the MTsat methods. These values are averaged within the gray matter and white matter masks.

Code imports#

# Python imports 
from IPython.display import clear_output
from pathlib import Path
import numpy as np

import pandas as pd
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.width', 1000)
pd.set_option('display.colheader_justify', 'center')
pd.set_option('display.precision', 1)

# Import custom tools
from tools.data import Data
from tools.plot import Plot
from tools.stats import Stats

Download data#

data_type = 'brain'
release_version = 'latest'

dataset = Data(data_type)
dataset.download(release_version)
--2022-09-21 14:50:44--  https://github.com/courtois-neuromod/anat-processing/releases/download/r20220921/neuromod-anat-brain-qmri.zip
Resolving github.com (github.com)... 140.82.114.3
Connecting to github.com (github.com)|140.82.114.3|:443... connected.
HTTP request sent, awaiting response... 
302 Found
Location: https://objects.githubusercontent.com/github-production-release-asset-2e65be/333825187/59a68bb3-4423-49ab-959d-247690acbebc?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20220921%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20220921T145044Z&X-Amz-Expires=300&X-Amz-Signature=10913a31cb50261413bb28b00551beffe5d3f0b42ec440e5b771403524176fc0&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=333825187&response-content-disposition=attachment%3B%20filename%3Dneuromod-anat-brain-qmri.zip&response-content-type=application%2Foctet-stream [following]
--2022-09-21 14:50:44--  https://objects.githubusercontent.com/github-production-release-asset-2e65be/333825187/59a68bb3-4423-49ab-959d-247690acbebc?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20220921%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20220921T145044Z&X-Amz-Expires=300&X-Amz-Signature=10913a31cb50261413bb28b00551beffe5d3f0b42ec440e5b771403524176fc0&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=333825187&response-content-disposition=attachment%3B%20filename%3Dneuromod-anat-brain-qmri.zip&response-content-type=application%2Foctet-stream
Resolving objects.githubusercontent.com (objects.githubusercontent.com)... 185.199.111.133, 185.199.108.133, 185.199.109.133, ...
Connecting to objects.githubusercontent.com (objects.githubusercontent.com)|185.199.111.133|:443... connected.
HTTP request sent, awaiting response... 200 OK
Length: 1301347 (1.2M) [application/octet-stream]
Saving to: ‘neuromod-anat-brain-qmri.zip’

     0K .......... .......... .......... .......... ..........  3% 3.28M 0s
    50K .......... .......... .......... .......... .....
Archive:  neuromod-anat-brain-qmri.zip
  inflating: data/brain/neuromod-anat-brain.nextflow.log  
  inflating: data/brain/results-neuromod-anat-brain-qmri.csv  
  inflating: data/brain/._results-neuromod-anat-brain-qmri.csv  
  inflating: data/brain/dag.dot      
  inflating: data/brain/report.html  
  inflating: data/brain/dag.png      
.....  7% 4.48M 0s
   100K .......... .......... .......... .......... .......... 11% 17.1M 0s
   150K .......... .......... .......... .......... .......... 15% 19.5M 0s
   200K .......... .......... .......... .......... .......... 19% 6.66M 0s
   250K .......... .......... .......... .......... .......... 23% 31.5M 0s
   300K .......... .......... .......... .......... .......... 27% 28.5M 0s
   350K .......... .......... .......... .......... .......... 31% 34.6M 0s
   400K .......... .......... .......... .......... .......... 35% 51.0M 0s
   450K .......... .......... .......... .......... .......... 39% 32.9M 0s
   500K .......... .......... .......... .......... .......... 43% 8.00M 0s
   550K .......... .......... .......... .......... .......... 47% 71.8M 0s
   600K .......... .......... .......... .......... .......... 51% 41.4M 0s
   650K .......... .......... .......... .......... .......... 55%  140M 0s
   700K .......... .......... .......... .......... .......... 59% 68.1M 0s
   750K .......... .......... .......... .......... .......... 62% 49.4M 0s
   800K .......... .......... .......... .......... .......... 66% 73.5M 0s
   850K .......... .......... .......... .......... .......... 70% 83.6M 0s
   900K .......... .......... .......... .......... .......... 74%  140M 0s
   950K .......... .......... .......... .......... .......... 78% 55.0M 0s
  1000K .......... .......... .......... .......... .......... 82% 7.37M 0s
  1050K .......... .......... .......... .......... .......... 86%  120M 0s
  1100K .......... .......... .......... .......... .......... 90%  131M 0s
  1150K .......... .......... .......... .......... .......... 94%  149M 0s
  1200K .......... .......... .......... .......... .......... 98%  129M 0s
  1250K .......... ..........                                 100% 87.9M=0.07s

2022-09-21 14:50:45 (18.7 MB/s) - ‘neuromod-anat-brain-qmri.zip’ saved [1301347/1301347]

Load data plot it#

qMRI Metrics#

dataset.load()
fig_gm = Plot(dataset, plot_name = 'brain-1')

fig_gm.title = 'Brain qMRI microstructure measures'
# If you're running this notebook in a Jupyter Notebook (eg, on MyBinder), change 'jupyter-book' to 'notebook'
fig_gm.display('jupyter-book')

Statistics#

White Matter#

stats_wm = Stats(dataset)
stats_wm.build_df('WM')
stats_wm.build_stats_table()
display(stats_wm.stats_table)
T1 (MP2RAGE) T1 (MTsat) MTR MTsat
intrasubject COV mean [%] 0.6 2.3 0.6 1.7
intrasubject COV std [%] 0.2 0.8 0.1 0.5
intersubject mean COV [%] 1.9 3.5 0.4 2.2

Grey Matter#

stats_gm = Stats(dataset)
stats_gm.build_df('GM')
stats_gm.build_stats_table()
display(stats_gm.stats_table)
T1 (MP2RAGE) T1 (MTsat) MTR MTsat
intrasubject COV mean [%] 0.4 3.1 0.8 2.7
intrasubject COV std [%] 0.1 1.6 0.2 1.2
intersubject mean COV [%] 1.0 5.7 1.2 4.5

Diffusion Tracts#

data_type = 'brain-diffusion'
release_version = 'latest'

dataset = Data(data_type)
dataset.download(release_version)

dataset.load()

fig_diff = Plot(dataset, plot_name = 'brain-diff')

fig_diff.title = 'Brain qMRI diffusion measures'

fig_diff.display('jupyter-book')
--2022-09-21 14:50:46--  https://github.com/courtois-neuromod/anat-processing/releases/download/r20220921b/brain-diffusion-arnaud.zip
Resolving github.com (github.com)... 140.82.114.3
Connecting to github.com (github.com)|140.82.114.3|:443... connected.
HTTP request sent, awaiting response... 
302 Found
Location: https://objects.githubusercontent.com/github-production-release-asset-2e65be/333825187/db2be019-9644-4ff2-8c70-c2d5347090b0?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20220921%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20220921T145046Z&X-Amz-Expires=300&X-Amz-Signature=3aa44b5c872171b8a37e15aeab71980ec45223cc8e5eb7e126903e430711bc3d&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=333825187&response-content-disposition=attachment%3B%20filename%3Dbrain-diffusion-arnaud.zip&response-content-type=application%2Foctet-stream [following]
--2022-09-21 14:50:46--  https://objects.githubusercontent.com/github-production-release-asset-2e65be/333825187/db2be019-9644-4ff2-8c70-c2d5347090b0?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAIWNJYAX4CSVEH53A%2F20220921%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20220921T145046Z&X-Amz-Expires=300&X-Amz-Signature=3aa44b5c872171b8a37e15aeab71980ec45223cc8e5eb7e126903e430711bc3d&X-Amz-SignedHeaders=host&actor_id=0&key_id=0&repo_id=333825187&response-content-disposition=attachment%3B%20filename%3Dbrain-diffusion-arnaud.zip&response-content-type=application%2Foctet-stream
Resolving objects.githubusercontent.com (objects.githubusercontent.com)... 185.199.110.133, 185.199.109.133, 185.199.108.133, ...
Connecting to objects.githubusercontent.com (objects.githubusercontent.com)|185.199.110.133|:443... connected.
HTTP request sent, awaiting response... 
200 OK
Length: 192601 (188K) [application/octet-stream]
Saving to: ‘brain-diffusion-arnaud.zip’

     0K .......... .......... .......... .......... .......... 26% 3.17M 0s
    50K .......... .......... .......... .......... .......... 53% 4.85M 0s
   100K .......... .......... .......... .......... .......... 79% 14.0M 0s
   150K .......... .......... .......... ........             100% 34.1M=0.03s

2022-09-21 14:50:47 (6.11 MB/s) - ‘brain-diffusion-arnaud.zip’ saved [192601/192601]
Archive:  brain-diffusion-arnaud.zip
  inflating: data/brain-diffusion/mean_std.json  
  inflating: data/brain-diffusion/._mean_std.json  
  inflating: data/brain-diffusion/volumes.json  
  inflating: data/brain-diffusion/._volumes.json  

Statistics#

stats_cc1 = Stats(dataset)
stats_cc1.build_df('CC_1')
stats_cc1.build_stats_table()
display(stats_cc1.stats_table)
FA (DWI) MD (DWI) RD (DWI)
intrasubject COV mean [%] 1.0 0.8 1.1
intrasubject COV std [%] 0.3 0.7 0.5
intersubject mean COV [%] 4.1 2.2 4.1
stats_mcp = Stats(dataset)
stats_mcp.build_df('MCP')
stats_mcp.build_stats_table()
display(stats_mcp.stats_table)
FA (DWI) MD (DWI) RD (DWI)
intrasubject COV mean [%] 1.1 1.0 1.6
intrasubject COV std [%] 0.4 0.3 0.4
intersubject mean COV [%] 6.7 2.4 6.3